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Qualitative And Quantitative Research - Coggle Diagram
Qualitative And Quantitative Research
Quantitative Research
sampling methods
random sampling
every member of the target population has an equal chance of participating
all possible characteristics are being taken into account, even when it is suspected not to play a role
hard to access large population, but it is simple and lacks biases
stratified sampling
one decides essential characteristics the sample has to reflect
one studies the distribution of these characteristics in the target population
participants are recruited so that the same proportions are in the sample as they are in the target population
theory-driven as the characteristics are fairly and equally represented in the sample.
opportunity sampling
recruit participants that are most easily available
good when resources are limited and it is believed that people are not different in terms of the phenomenon.
bad when generalization or representativeness is needed
self-selected sampling
recruiting volunteers
quick and easy way to recruit, while also having large coverage as many people read newspapers
often these samples consist of people who have taken part in a research before, making the study less good for generalization
credibility and generalizability
validity
construct validity
the extent to which your test or measure accurately assesses what it's supposed to
internal validity
Internal validity examines whether the study design, conduct, and analysis answer the research questions without bias
is the study reliable????
external validity
generalizability
can be divided into two
ecological
findings can be generalized to other settings or situations
if the setting is artificial, the ecological validity is low
bias might occur if ecological validity is too high as well as struggle to control confounding variables
popular
how well the findings can be generalized to the entire target population
bias
selection
when for some reason groups aren't equivalent at the start of the experiment
history
refers to the outside events that happen to participants in the course of the experiment
important when DV is measured sometime after the onset of the study
maturation
participants go through natural developmental processes, such as fatigue or simply growth
if the results are because of IV or just natural growth
testing effect
first measurement of the DV may affect the second measurement
instrumentation
when instrument(e.g. observer’s attention) changes between measurements
regression to the mean
experimental mortality
participants drop out
demand characteristics
participants understand the purpose of the experiment
experimenter bias
researcher unintentionally exerts an influence on the results of the experiments
experimental designs
independent measures design
random allocation of participants into groups and then comparing those groups
divided into control group and experimental group
an experimental design where different participants are used in each condition of the independent variable. This means that each condition of the experiment includes a different group of participants.
matched pairs design
similar to independent measures design, only difference is that the people are matched when forming the groups
participants are matched based on key variables, or shared characteristics, relevant to the topic of the study.
repeated measures design
when comparing (two or more) conditions on the same participants
results might differ depending on which one comes first
counterbalancing
: another group takes the conditions in reverse
strength is that participants are being compared to themselves so
participant variability
doesn't influence the results
correlational studies
Qualitative Research
generalizability
sample-to-population generalization
theoretical generalization
observation to theory
case-to-case generalization
generalization from different group of people or a different setting/context
sampling methods
quota sampling
prior to the start of the research the sample size and desired characteristics are determined
purposive sampling
the main characteristics of the sample are pre-defined but not the sample size
snowball sampling
small number of participants are invited and then asked to invite other people who might fit the participant group's desired characteristics
used for samples that are otherwise hard to reach (drug users, gang members)
convenience sampling
when the research uses the sample that is easily available
theoretical sampling
special sampling method when the sampling stops when the point of data saturation is reached
credility
equivalent to internal validity in the experimental method
trianqulation
when a combination of different methods is used
method triangulation
use of different methods so that individual limitations get eliminated
data triangulation
use of different data to get wider understanding
research triangulation
use of observations and analysis of multiple researchers
theory triangulation
use of multiple perspectives or theories to interpret the data
establishing a rapport
ensuring participants' honesty
reminding about voluntary participation
there are no right or wrong answers
this establishes an understanding between the researcher and the participant so that the latter feels comfortable to give truthful answers
iterative questioning
participants distort the data intentionally (lying) or unintentionally
when such behavior is spotted, researcher should come back to the question by rephrasing it so that deeper insight is acquired
reflexivity
researcher reflects on their own biases and how they might interfere with the observations
personal reflexivity
researcher is aware of one's own bias in the observations
epistemological reflexivity
researcher knows the strengths and limitations of the method and how it might affect the participants and the reflection
credibility checks
refers to checking accuracy of data by asking participants to read the transcripts and see if the interpretations of what they said or did were correct or if something was misunderstood
"thick descriptions"
when the observed behavior is not just observed but also the context and situation in which it occurred
research methods
observation
laboratory vs naturalistic observation
overt or covert observation
overt when participants are aware that they are being observed
participant observation
structured vs unstructured observation
interview
structured interviews
semi-structured interviews
unstructured interviews
focus group
content analysis
case study
in-depth investigation of an individual or a group
usually concenrate on unique cases, so not generalizable, often longitudinal
ethics
reporting results
data fabrication
plagiarism
publication credit
sharing research data for verification
handling of sensitive personal information
genetic research
mental disorders
social implications of reporting scientific results
conducting the study
informed consent
protection from harm
anonymity and confidentiality
withdrawal from participation
deception
debriefing
representativeness
:the fact of a smaller group of people or things representing a larger group accurately, so that the smaller group is typical of the larger one
